RRepoGEO

REPOGEO REPORT · LITE

hofstadter-io/hof

Default branch _next · commit 52feda8c · scanned 6/2/2026, 8:36:22 AM

GitHub: 608 stars · 47 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface hofstadter-io/hof, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening statement to clarify Hof's unique, CUE-powered unification role

    Why:

    CURRENT
    A tool that unifies data models, schemas, code generation, and a task engine.
    COPY-PASTE FIX
    A CUE-powered framework that unifies declarative schemas, data models, deterministic and agentic code generation, and a robust task engine into a single, cohesive developer workflow.
  • mediumtopics#2
    Add conceptual topics to emphasize unification and data-driven development

    Why:

    CURRENT
    adk-go, agents, cli, code-generator, cuelang, dagger, data-modeling, llms, schemas, tui, vscode-extension, workflow-engine
    COPY-PASTE FIX
    adk-go, agents, cli, code-generator, cuelang, dagger, data-modeling, llms, schemas, tui, vscode-extension, workflow-engine, declarative-programming, unified-workflow, data-driven-development
  • mediumreadme#3
    Add a 'Why Hof?' section to explicitly differentiate from common alternatives

    Why:

    COPY-PASTE FIX
    ### Why Hof?
Unlike standalone schema tools like GraphQL or pure LLM orchestration frameworks, Hof provides a unified, CUE-powered platform for defining, generating, and managing code and data across your entire development workflow, ensuring consistency and reducing boilerplate through its deterministic and agentic capabilities.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface hofstadter-io/hof
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GraphQL
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GraphQL · recommended 1×
  2. GraphQL Code Generator · recommended 1×
  3. Apollo Codegen · recommended 1×
  4. Apollo Client · recommended 1×
  5. Prisma · recommended 1×
  • CATEGORY QUERY
    How to unify declarative schemas, data models, and code generation in a single workflow?
    you: not recommended
    AI recommended (in order):
    1. GraphQL
    2. GraphQL Code Generator
    3. Apollo Codegen
    4. Apollo Client
    5. Prisma
    6. Nexus
    7. Pothos
    8. OpenAPI
    9. Swagger
    10. OpenAPI Generator
    11. NSwag
    12. JSON Schema
    13. quicktype
    14. json-schema-to-typescript
    15. SQLAlchemy
    16. Alembic
    17. Entity Framework Core
    18. Entity Framework Core Migrations
    19. Protocol Buffers
    20. Apache Avro
    21. gRPC

    AI recommended 21 alternatives but never named hofstadter-io/hof. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help build complex data-driven workflows with agentic code generation capabilities?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. BabyAGI
    5. CrewAI
    6. Prefect
    7. Apache Airflow
    8. Kubeflow Pipelines
    9. Dagster
    10. Microsoft Semantic Kernel

    AI recommended 10 alternatives but never named hofstadter-io/hof. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of hofstadter-io/hof?
    pass
    AI named hofstadter-io/hof explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts hofstadter-io/hof in production, what risks or prerequisites should they evaluate first?
    pass
    AI named hofstadter-io/hof explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo hofstadter-io/hof solve, and who is the primary audience?
    pass
    AI named hofstadter-io/hof explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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hofstadter-io/hof — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite